1. Field of the Invention
The present invention relates to a method and system for recommending research information news, in particular to one which uses a judging timing to divide the research documents into early and new recent research documents, then uses the computer system to gather statistics of the linguistic units of the research documents and make analysis to generate research keywords, and thence filters out the research keywords of the new recent research documents repeating those of the early research documents, thereby obtaining the new recent research keywords.
2. Description of the Related Art
Following the coming of the intellectual economic time, the academic innovation technique is updated more quickly and becomes pluralistic to cause the screening and selecting of the academic releases to become an extremely challengeable issue.
Therefore, a prior technique published by Taiwan patent no. 201314477 and titled by “an analytical method and system for hot and foreseeing R&D information” is disclosed. The system comprises a processing unit, a database analytical subsystem, a database module, a hot research analysis subsystem, a foreseeing research analysis subsystem, a factor evaluation subsystem, a hot research verification subsystem, a foreseeing research verification subsystem, and a search and browser subsystem. The processing unit includes an operating interface and a display interface. The database analytical subsystem is built in the processing unit. The database analytical subsystem comprises an editing and managing module and a data processing module for importing an external data. By using the system, the operating interface is applied to select the academic document derived from a particular year range, such as a year range n and set by n≦2 or 5≦n≦10, then the foreseeing research analysis subsystem or the hot research analysis subsystem uses a TF-IDF surveying technique to gather statistics of the number of appearing times of the technical keywords of the academic documents within the selected particular year range. Thence the foreseeing indexes or hot indexes of these academic documents can be analyzed to assist users in selecting foreseeable or hot academic documents.
However, the prior art still needs improvements with the reasons:
1. The prior technique must use the particular hot or foreseeable keywords and cooperate with the TF-IDF surveying technique to gather statistic of the number of appearing times of the technical keywords of the academic documents within the particular year range to analyze and obtain the foreseeing or the hot indexes. The prior technique cannot be a suitable analysis condition as users unfamiliar with the related keywords of the field cannot use proper keywords easily.
2. The prior technique can only find out the distinct and critical words from the academic documents but cannot find out the novel or hot words which are not distinct but critical to the technique.
3. The prior system cannot help users find out the author who makes the most contribution to the research document when it is applied to the news field since large numbers of authors participating in the research document would cause the user to have difficulty in interviewing the author in case the system does not help the screening operation.